{"title":"视网膜图像中血管的自动检测","authors":"A. Elbalaoui, M. Fakir, K. Taifi, A. Merbouha","doi":"10.4018/IJHISI.2017010102","DOIUrl":null,"url":null,"abstract":"Automatic detection of retinal blood vessels and measurement of vessel diameter are very much important for the diagnosis and the treatment of different ocular diseases including diabetic retinopathy (DR), glaucoma and hypertension. In this paper, we present a novel method to detect blood vessels in the fundus retinal images. The proposed method consists of three main steps. The first step is pre-processing of retinal image to improve the retinal images by evaluation of several image enhancement techniques. In the second step, the vesselness filter is usually used to enhance the blood vessels. Finally Hessian multiscale enhancement filter is designed from the adaptive thresholding of the output of the vesselness filter for vessels detection. The performance of algorithms is compared and analyzed on three publicly available databases (DRIVE, STARE and CHASE_DB) of retinal images using a number of measures, which include accuracy, sensitivity, and specificity.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"410 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":"{\"title\":\"Automatic Detection of Blood Vessel in Retinal Images\",\"authors\":\"A. Elbalaoui, M. Fakir, K. Taifi, A. Merbouha\",\"doi\":\"10.4018/IJHISI.2017010102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automatic detection of retinal blood vessels and measurement of vessel diameter are very much important for the diagnosis and the treatment of different ocular diseases including diabetic retinopathy (DR), glaucoma and hypertension. In this paper, we present a novel method to detect blood vessels in the fundus retinal images. The proposed method consists of three main steps. The first step is pre-processing of retinal image to improve the retinal images by evaluation of several image enhancement techniques. In the second step, the vesselness filter is usually used to enhance the blood vessels. Finally Hessian multiscale enhancement filter is designed from the adaptive thresholding of the output of the vesselness filter for vessels detection. The performance of algorithms is compared and analyzed on three publicly available databases (DRIVE, STARE and CHASE_DB) of retinal images using a number of measures, which include accuracy, sensitivity, and specificity.\",\"PeriodicalId\":351561,\"journal\":{\"name\":\"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)\",\"volume\":\"410 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"33\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJHISI.2017010102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJHISI.2017010102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Detection of Blood Vessel in Retinal Images
Automatic detection of retinal blood vessels and measurement of vessel diameter are very much important for the diagnosis and the treatment of different ocular diseases including diabetic retinopathy (DR), glaucoma and hypertension. In this paper, we present a novel method to detect blood vessels in the fundus retinal images. The proposed method consists of three main steps. The first step is pre-processing of retinal image to improve the retinal images by evaluation of several image enhancement techniques. In the second step, the vesselness filter is usually used to enhance the blood vessels. Finally Hessian multiscale enhancement filter is designed from the adaptive thresholding of the output of the vesselness filter for vessels detection. The performance of algorithms is compared and analyzed on three publicly available databases (DRIVE, STARE and CHASE_DB) of retinal images using a number of measures, which include accuracy, sensitivity, and specificity.